Dietary soy and meat proteins induce distinct physiological and gene expression changes in rats View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-04

AUTHORS

Shangxin Song, Guido J Hooiveld, Mengjie Li, Fan Zhao, Wei Zhang, Xinglian Xu, Michael Muller, Chunbao Li, Guanghong Zhou

ABSTRACT

This study reports on a comprehensive comparison of the effects of soy and meat proteins given at the recommended level on physiological markers of metabolic syndrome and the hepatic transcriptome. Male rats were fed semi-synthetic diets for 1 wk that differed only regarding protein source, with casein serving as reference. Body weight gain and adipose tissue mass were significantly reduced by soy but not meat proteins. The insulin resistance index was improved by soy, and to a lesser extent by meat proteins. Liver triacylglycerol contents were reduced by both protein sources, which coincided with increased plasma triacylglycerol concentrations. Both soy and meat proteins changed plasma amino acid patterns. The expression of 1571 and 1369 genes were altered by soy and meat proteins respectively. Functional classification revealed that lipid, energy and amino acid metabolic pathways, as well as insulin signaling pathways were regulated differently by soy and meat proteins. Several transcriptional regulators, including NFE2L2, ATF4, Srebf1 and Rictor were identified as potential key upstream regulators. These results suggest that soy and meat proteins induce distinct physiological and gene expression responses in rats and provide novel evidence and suggestions for the health effects of different protein sources in human diets. More... »

PAGES

20036

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep20036

DOI

http://dx.doi.org/10.1038/srep20036

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1006782067

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26857845


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0601", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biochemistry and Cell Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Animals", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Diet", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Dietary Proteins", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Expression Profiling", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Expression Regulation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Meat", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Metabolic Networks and Pathways", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Rats", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Rats, Sprague-Dawley", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Signal Transduction", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Soybean Proteins", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Nanjing Agricultural University", 
          "id": "https://www.grid.ac/institutes/grid.27871.3b", 
          "name": [
            "Key Laboratory of Meat Processing and Quality Control, MOE; Key Laboratory of Animal Products Processing, MOA; Jiang Synergetic Innovation Center of Meat Processing and Quality Control; Nanjing Agricultural University, Nanjing 210095, P.R. China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Song", 
        "givenName": "Shangxin", 
        "id": "sg:person.01317542531.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01317542531.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Wageningen University & Research", 
          "id": "https://www.grid.ac/institutes/grid.4818.5", 
          "name": [
            "Nutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen University, Wageningen, the Netherlands."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hooiveld", 
        "givenName": "Guido J", 
        "id": "sg:person.01054123502.11", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01054123502.11"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nanjing Agricultural University", 
          "id": "https://www.grid.ac/institutes/grid.27871.3b", 
          "name": [
            "Key Laboratory of Meat Processing and Quality Control, MOE; Key Laboratory of Animal Products Processing, MOA; Jiang Synergetic Innovation Center of Meat Processing and Quality Control; Nanjing Agricultural University, Nanjing 210095, P.R. China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Li", 
        "givenName": "Mengjie", 
        "id": "sg:person.01342637653.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01342637653.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nanjing Agricultural University", 
          "id": "https://www.grid.ac/institutes/grid.27871.3b", 
          "name": [
            "Key Laboratory of Meat Processing and Quality Control, MOE; Key Laboratory of Animal Products Processing, MOA; Jiang Synergetic Innovation Center of Meat Processing and Quality Control; Nanjing Agricultural University, Nanjing 210095, P.R. China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhao", 
        "givenName": "Fan", 
        "id": "sg:person.0617233553.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0617233553.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nanjing Medical University", 
          "id": "https://www.grid.ac/institutes/grid.89957.3a", 
          "name": [
            "Key Laboratory of Human Function Genomics Jiangsu Province, Nanjing Medical University, Nanjing, 210029, P.R. China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Wei", 
        "id": "sg:person.01270260045.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01270260045.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nanjing Agricultural University", 
          "id": "https://www.grid.ac/institutes/grid.27871.3b", 
          "name": [
            "Key Laboratory of Meat Processing and Quality Control, MOE; Key Laboratory of Animal Products Processing, MOA; Jiang Synergetic Innovation Center of Meat Processing and Quality Control; Nanjing Agricultural University, Nanjing 210095, P.R. China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xu", 
        "givenName": "Xinglian", 
        "id": "sg:person.0764176271.21", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0764176271.21"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of East Anglia", 
          "id": "https://www.grid.ac/institutes/grid.8273.e", 
          "name": [
            "Norwich Medical School, University of East Anglia Norwich, Norwich, UK."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Muller", 
        "givenName": "Michael", 
        "id": "sg:person.010546431340.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010546431340.44"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nanjing Agricultural University", 
          "id": "https://www.grid.ac/institutes/grid.27871.3b", 
          "name": [
            "Key Laboratory of Meat Processing and Quality Control, MOE; Key Laboratory of Animal Products Processing, MOA; Jiang Synergetic Innovation Center of Meat Processing and Quality Control; Nanjing Agricultural University, Nanjing 210095, P.R. China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Li", 
        "givenName": "Chunbao", 
        "id": "sg:person.01337312751.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01337312751.35"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Nanjing Agricultural University", 
          "id": "https://www.grid.ac/institutes/grid.27871.3b", 
          "name": [
            "Key Laboratory of Meat Processing and Quality Control, MOE; Key Laboratory of Animal Products Processing, MOA; Jiang Synergetic Innovation Center of Meat Processing and Quality Control; Nanjing Agricultural University, Nanjing 210095, P.R. China."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhou", 
        "givenName": "Guanghong", 
        "id": "sg:person.01261752723.94", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261752723.94"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1152/ajpendo.90207.2008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000726018"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/physiolgenomics.00263.2007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002356517"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.meatsci.2012.09.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003640702"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.nutr.27.061406.093726", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004776463"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0954422411000175", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004938160"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0013984", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006850384"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11883-013-0348-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008674288", 
          "https://doi.org/10.1007/s11883-013-0348-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1530/joe-13-0327", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010137250"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.yexcr.2007.07.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011058023"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0914005107", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011637541"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep06697", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012347119", 
          "https://doi.org/10.1038/srep06697"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkv007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016098431"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrm3522", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021975364", 
          "https://doi.org/10.1038/nrm3522"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.meatsci.2004.11.021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022120696"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkt1168", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023238985"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btp616", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023247882"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-10-275", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024605858", 
          "https://doi.org/10.1186/1471-2105-10-275"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep10604", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025197679", 
          "https://doi.org/10.1038/srep10604"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11154-013-9251-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025487619", 
          "https://doi.org/10.1007/s11154-013-9251-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrm3757", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027076437", 
          "https://doi.org/10.1038/nrm3757"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.molcel.2013.01.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029235010"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5713/ajas.2011.10430", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029355555"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.nut.2006.06.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029776547"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0047303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032907060"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jnutbio.2007.09.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034255641"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/mol.0b013e3283613bb7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034869172"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/mol.0b013e3283613bb7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034869172"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biochi.2010.02.020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034904850"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.plipres.2010.10.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035064833"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1079/pns19720050", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037137050"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1079/pns19720050", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037137050"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0506580102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037705714"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0506580102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037705714"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1074/jbc.m701045200", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040707347"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/bioinformatics/btu781", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041244887"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ng0508-523", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045250677", 
          "https://doi.org/10.1038/ng0508-523"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2014-15-2-r29", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045312009", 
          "https://doi.org/10.1186/gb-2014-15-2-r29"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-0-12-800101-1.00011-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045436662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-0-12-800101-1.00011-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045436662"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/pmic.201500179", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046487171"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biochi.2004.09.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048218799"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tem.2009.05.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050160159"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/db12-1613", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050295819"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/db12-1613", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050295819"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0007114512002565", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050308774"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2010-11-3-r25", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050509557", 
          "https://doi.org/10.1186/gb-2010-11-3-r25"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cmet.2012.03.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051276341"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-0-12-416555-7.00001-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052423436"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/0884533614550251", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053801329"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf0009246", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055896283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf0009246", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055896283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf0481103", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055902573"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf0481103", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055902573"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf901954r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055926938"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf901954r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055926938"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2527/jas1962.213558x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1070893028"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jn/122.3.467", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1076919383"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1079/bjn20061895", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1077303393"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078059471", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.29074/ascls.23.1.51", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078059471"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1080446225", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jn/96.3.303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1081294691"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jn/125.3_suppl.594s", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082550318"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jn/125.3_suppl.606s", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082550320"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jn/123.11.1939", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082711967"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jn/127.5.758", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083095112"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jn/128.7.1084", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083285733"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-04", 
    "datePublishedReg": "2016-04-01", 
    "description": "This study reports on a comprehensive comparison of the effects of soy and meat proteins given at the recommended level on physiological markers of metabolic syndrome and the hepatic transcriptome. Male rats were fed semi-synthetic diets for 1 wk that differed only regarding protein source, with casein serving as reference. Body weight gain and adipose tissue mass were significantly reduced by soy but not meat proteins. The insulin resistance index was improved by soy, and to a lesser extent by meat proteins. Liver triacylglycerol contents were reduced by both protein sources, which coincided with increased plasma triacylglycerol concentrations. Both soy and meat proteins changed plasma amino acid patterns. The expression of 1571 and 1369 genes were altered by soy and meat proteins respectively. Functional classification revealed that lipid, energy and amino acid metabolic pathways, as well as insulin signaling pathways were regulated differently by soy and meat proteins. Several transcriptional regulators, including NFE2L2, ATF4, Srebf1 and Rictor were identified as potential key upstream regulators. These results suggest that soy and meat proteins induce distinct physiological and gene expression responses in rats and provide novel evidence and suggestions for the health effects of different protein sources in human diets. ", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/srep20036", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "6"
      }
    ], 
    "name": "Dietary soy and meat proteins induce distinct physiological and gene expression changes in rats", 
    "pagination": "20036", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "204e2310d20136fdeb5114e3e25f6b07e7e7c6aee7b7109b776039d65cd22f81"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "26857845"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/srep20036"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1006782067"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/srep20036", 
      "https://app.dimensions.ai/details/publication/pub.1006782067"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T14:16", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8660_00000549.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://www.nature.com/srep/2016/160209/srep20036/full/srep20036.html"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/srep20036'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/srep20036'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/srep20036'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/srep20036'


 

This table displays all metadata directly associated to this object as RDF triples.

366 TRIPLES      21 PREDICATES      100 URIs      33 LITERALS      21 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/srep20036 schema:about N2331f6cdfff3461d923ee1b10fdca58a
2 N3e52017e0b6c4bab862b0b94a71c6999
3 N413c1e20eeab492a80d50e1433260b79
4 N7ad9546812e44a4db34cea791b51dcbe
5 N888f3929f78445a5b156648bdff9d2f2
6 N8b81c741cb434ab99b71743cc3dad2b4
7 Nbd759b4e66b04b319305eb544c31f8c8
8 Nc5c53bc81cb44192a71e124fba020b66
9 Ndc3f917f26d44b8eacf828492ae96399
10 Ndeb4c90f7a9541d3ac072ad846a6b887
11 Ne4780330095a4d0aa551503edeab4cda
12 Nec7110a8f34d47c29448ed758550e7b8
13 anzsrc-for:06
14 anzsrc-for:0601
15 schema:author N5f8c9f35d2ff489080b89c4822a96cb8
16 schema:citation sg:pub.10.1007/s11154-013-9251-y
17 sg:pub.10.1007/s11883-013-0348-2
18 sg:pub.10.1038/ng0508-523
19 sg:pub.10.1038/nrm3522
20 sg:pub.10.1038/nrm3757
21 sg:pub.10.1038/srep06697
22 sg:pub.10.1038/srep10604
23 sg:pub.10.1186/1471-2105-10-275
24 sg:pub.10.1186/gb-2010-11-3-r25
25 sg:pub.10.1186/gb-2014-15-2-r29
26 https://app.dimensions.ai/details/publication/pub.1078059471
27 https://app.dimensions.ai/details/publication/pub.1080446225
28 https://doi.org/10.1002/pmic.201500179
29 https://doi.org/10.1016/b978-0-12-416555-7.00001-1
30 https://doi.org/10.1016/b978-0-12-800101-1.00011-9
31 https://doi.org/10.1016/j.biochi.2004.09.018
32 https://doi.org/10.1016/j.biochi.2010.02.020
33 https://doi.org/10.1016/j.cmet.2012.03.015
34 https://doi.org/10.1016/j.jnutbio.2007.09.003
35 https://doi.org/10.1016/j.meatsci.2004.11.021
36 https://doi.org/10.1016/j.meatsci.2012.09.018
37 https://doi.org/10.1016/j.molcel.2013.01.019
38 https://doi.org/10.1016/j.nut.2006.06.009
39 https://doi.org/10.1016/j.plipres.2010.10.004
40 https://doi.org/10.1016/j.tem.2009.05.008
41 https://doi.org/10.1016/j.yexcr.2007.07.017
42 https://doi.org/10.1017/s0007114512002565
43 https://doi.org/10.1017/s0954422411000175
44 https://doi.org/10.1021/jf0009246
45 https://doi.org/10.1021/jf0481103
46 https://doi.org/10.1021/jf901954r
47 https://doi.org/10.1073/pnas.0506580102
48 https://doi.org/10.1073/pnas.0914005107
49 https://doi.org/10.1074/jbc.m701045200
50 https://doi.org/10.1079/bjn20061895
51 https://doi.org/10.1079/pns19720050
52 https://doi.org/10.1093/bioinformatics/btp616
53 https://doi.org/10.1093/bioinformatics/btu781
54 https://doi.org/10.1093/jn/122.3.467
55 https://doi.org/10.1093/jn/123.11.1939
56 https://doi.org/10.1093/jn/125.3_suppl.594s
57 https://doi.org/10.1093/jn/125.3_suppl.606s
58 https://doi.org/10.1093/jn/127.5.758
59 https://doi.org/10.1093/jn/128.7.1084
60 https://doi.org/10.1093/jn/96.3.303
61 https://doi.org/10.1093/nar/gkt1168
62 https://doi.org/10.1093/nar/gkv007
63 https://doi.org/10.1097/mol.0b013e3283613bb7
64 https://doi.org/10.1146/annurev.nutr.27.061406.093726
65 https://doi.org/10.1152/ajpendo.90207.2008
66 https://doi.org/10.1152/physiolgenomics.00263.2007
67 https://doi.org/10.1177/0884533614550251
68 https://doi.org/10.1371/journal.pone.0013984
69 https://doi.org/10.1371/journal.pone.0047303
70 https://doi.org/10.1530/joe-13-0327
71 https://doi.org/10.2337/db12-1613
72 https://doi.org/10.2527/jas1962.213558x
73 https://doi.org/10.29074/ascls.23.1.51
74 https://doi.org/10.5713/ajas.2011.10430
75 schema:datePublished 2016-04
76 schema:datePublishedReg 2016-04-01
77 schema:description This study reports on a comprehensive comparison of the effects of soy and meat proteins given at the recommended level on physiological markers of metabolic syndrome and the hepatic transcriptome. Male rats were fed semi-synthetic diets for 1 wk that differed only regarding protein source, with casein serving as reference. Body weight gain and adipose tissue mass were significantly reduced by soy but not meat proteins. The insulin resistance index was improved by soy, and to a lesser extent by meat proteins. Liver triacylglycerol contents were reduced by both protein sources, which coincided with increased plasma triacylglycerol concentrations. Both soy and meat proteins changed plasma amino acid patterns. The expression of 1571 and 1369 genes were altered by soy and meat proteins respectively. Functional classification revealed that lipid, energy and amino acid metabolic pathways, as well as insulin signaling pathways were regulated differently by soy and meat proteins. Several transcriptional regulators, including NFE2L2, ATF4, Srebf1 and Rictor were identified as potential key upstream regulators. These results suggest that soy and meat proteins induce distinct physiological and gene expression responses in rats and provide novel evidence and suggestions for the health effects of different protein sources in human diets.
78 schema:genre research_article
79 schema:inLanguage en
80 schema:isAccessibleForFree true
81 schema:isPartOf N5313a539ca8f4b1fa80dc5a6b38e7291
82 N8c9b0ebfda6d48fea0c17534a1a791a8
83 sg:journal.1045337
84 schema:name Dietary soy and meat proteins induce distinct physiological and gene expression changes in rats
85 schema:pagination 20036
86 schema:productId N59f19077c8f14652b11f6a3295479028
87 N904b7edbefbe4f15a772009b28f5bee8
88 Na6ce512509d24113b1fd643266460e3c
89 Nb47976f8d43b45aa9c277b613fa019ec
90 Nefdf8ade3779447b85d77268b5463d6a
91 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006782067
92 https://doi.org/10.1038/srep20036
93 schema:sdDatePublished 2019-04-10T14:16
94 schema:sdLicense https://scigraph.springernature.com/explorer/license/
95 schema:sdPublisher N8b7f48a3b0524296a2c078a48fc7f1c4
96 schema:url http://www.nature.com/srep/2016/160209/srep20036/full/srep20036.html
97 sgo:license sg:explorer/license/
98 sgo:sdDataset articles
99 rdf:type schema:ScholarlyArticle
100 N0595257bb4a8455ca585cf41daa8b18b rdf:first sg:person.01270260045.52
101 rdf:rest N31614932b4284e7a91ce8cad814d65ce
102 N06ffb6ca7bae46aeb3e64466d6ff324f rdf:first sg:person.010546431340.44
103 rdf:rest N4961526391c2449b9dee99e2727b8575
104 N2331f6cdfff3461d923ee1b10fdca58a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
105 schema:name Soybean Proteins
106 rdf:type schema:DefinedTerm
107 N31614932b4284e7a91ce8cad814d65ce rdf:first sg:person.0764176271.21
108 rdf:rest N06ffb6ca7bae46aeb3e64466d6ff324f
109 N32d4758bb00d43b1a816ff4c14a0be27 rdf:first sg:person.01342637653.18
110 rdf:rest N54fa15d47ee949049f0eae4abaaaefb1
111 N3e52017e0b6c4bab862b0b94a71c6999 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
112 schema:name Signal Transduction
113 rdf:type schema:DefinedTerm
114 N413c1e20eeab492a80d50e1433260b79 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Rats
116 rdf:type schema:DefinedTerm
117 N4961526391c2449b9dee99e2727b8575 rdf:first sg:person.01337312751.35
118 rdf:rest N4d0afc7234f64e91a0a706eec25acd79
119 N4d0afc7234f64e91a0a706eec25acd79 rdf:first sg:person.01261752723.94
120 rdf:rest rdf:nil
121 N5313a539ca8f4b1fa80dc5a6b38e7291 schema:volumeNumber 6
122 rdf:type schema:PublicationVolume
123 N54fa15d47ee949049f0eae4abaaaefb1 rdf:first sg:person.0617233553.37
124 rdf:rest N0595257bb4a8455ca585cf41daa8b18b
125 N59f19077c8f14652b11f6a3295479028 schema:name nlm_unique_id
126 schema:value 101563288
127 rdf:type schema:PropertyValue
128 N5f8c9f35d2ff489080b89c4822a96cb8 rdf:first sg:person.01317542531.50
129 rdf:rest N8ea4c2606886460a8e59a2e983ba7e17
130 N7ad9546812e44a4db34cea791b51dcbe schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
131 schema:name Diet
132 rdf:type schema:DefinedTerm
133 N888f3929f78445a5b156648bdff9d2f2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Dietary Proteins
135 rdf:type schema:DefinedTerm
136 N8b7f48a3b0524296a2c078a48fc7f1c4 schema:name Springer Nature - SN SciGraph project
137 rdf:type schema:Organization
138 N8b81c741cb434ab99b71743cc3dad2b4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Metabolic Networks and Pathways
140 rdf:type schema:DefinedTerm
141 N8c9b0ebfda6d48fea0c17534a1a791a8 schema:issueNumber 1
142 rdf:type schema:PublicationIssue
143 N8ea4c2606886460a8e59a2e983ba7e17 rdf:first sg:person.01054123502.11
144 rdf:rest N32d4758bb00d43b1a816ff4c14a0be27
145 N904b7edbefbe4f15a772009b28f5bee8 schema:name readcube_id
146 schema:value 204e2310d20136fdeb5114e3e25f6b07e7e7c6aee7b7109b776039d65cd22f81
147 rdf:type schema:PropertyValue
148 Na6ce512509d24113b1fd643266460e3c schema:name dimensions_id
149 schema:value pub.1006782067
150 rdf:type schema:PropertyValue
151 Nb47976f8d43b45aa9c277b613fa019ec schema:name pubmed_id
152 schema:value 26857845
153 rdf:type schema:PropertyValue
154 Nbd759b4e66b04b319305eb544c31f8c8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Gene Expression Profiling
156 rdf:type schema:DefinedTerm
157 Nc5c53bc81cb44192a71e124fba020b66 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
158 schema:name Male
159 rdf:type schema:DefinedTerm
160 Ndc3f917f26d44b8eacf828492ae96399 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
161 schema:name Meat
162 rdf:type schema:DefinedTerm
163 Ndeb4c90f7a9541d3ac072ad846a6b887 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
164 schema:name Animals
165 rdf:type schema:DefinedTerm
166 Ne4780330095a4d0aa551503edeab4cda schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
167 schema:name Rats, Sprague-Dawley
168 rdf:type schema:DefinedTerm
169 Nec7110a8f34d47c29448ed758550e7b8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
170 schema:name Gene Expression Regulation
171 rdf:type schema:DefinedTerm
172 Nefdf8ade3779447b85d77268b5463d6a schema:name doi
173 schema:value 10.1038/srep20036
174 rdf:type schema:PropertyValue
175 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
176 schema:name Biological Sciences
177 rdf:type schema:DefinedTerm
178 anzsrc-for:0601 schema:inDefinedTermSet anzsrc-for:
179 schema:name Biochemistry and Cell Biology
180 rdf:type schema:DefinedTerm
181 sg:journal.1045337 schema:issn 2045-2322
182 schema:name Scientific Reports
183 rdf:type schema:Periodical
184 sg:person.01054123502.11 schema:affiliation https://www.grid.ac/institutes/grid.4818.5
185 schema:familyName Hooiveld
186 schema:givenName Guido J
187 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01054123502.11
188 rdf:type schema:Person
189 sg:person.010546431340.44 schema:affiliation https://www.grid.ac/institutes/grid.8273.e
190 schema:familyName Muller
191 schema:givenName Michael
192 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010546431340.44
193 rdf:type schema:Person
194 sg:person.01261752723.94 schema:affiliation https://www.grid.ac/institutes/grid.27871.3b
195 schema:familyName Zhou
196 schema:givenName Guanghong
197 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261752723.94
198 rdf:type schema:Person
199 sg:person.01270260045.52 schema:affiliation https://www.grid.ac/institutes/grid.89957.3a
200 schema:familyName Zhang
201 schema:givenName Wei
202 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01270260045.52
203 rdf:type schema:Person
204 sg:person.01317542531.50 schema:affiliation https://www.grid.ac/institutes/grid.27871.3b
205 schema:familyName Song
206 schema:givenName Shangxin
207 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01317542531.50
208 rdf:type schema:Person
209 sg:person.01337312751.35 schema:affiliation https://www.grid.ac/institutes/grid.27871.3b
210 schema:familyName Li
211 schema:givenName Chunbao
212 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01337312751.35
213 rdf:type schema:Person
214 sg:person.01342637653.18 schema:affiliation https://www.grid.ac/institutes/grid.27871.3b
215 schema:familyName Li
216 schema:givenName Mengjie
217 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01342637653.18
218 rdf:type schema:Person
219 sg:person.0617233553.37 schema:affiliation https://www.grid.ac/institutes/grid.27871.3b
220 schema:familyName Zhao
221 schema:givenName Fan
222 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0617233553.37
223 rdf:type schema:Person
224 sg:person.0764176271.21 schema:affiliation https://www.grid.ac/institutes/grid.27871.3b
225 schema:familyName Xu
226 schema:givenName Xinglian
227 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0764176271.21
228 rdf:type schema:Person
229 sg:pub.10.1007/s11154-013-9251-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1025487619
230 https://doi.org/10.1007/s11154-013-9251-y
231 rdf:type schema:CreativeWork
232 sg:pub.10.1007/s11883-013-0348-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008674288
233 https://doi.org/10.1007/s11883-013-0348-2
234 rdf:type schema:CreativeWork
235 sg:pub.10.1038/ng0508-523 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045250677
236 https://doi.org/10.1038/ng0508-523
237 rdf:type schema:CreativeWork
238 sg:pub.10.1038/nrm3522 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021975364
239 https://doi.org/10.1038/nrm3522
240 rdf:type schema:CreativeWork
241 sg:pub.10.1038/nrm3757 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027076437
242 https://doi.org/10.1038/nrm3757
243 rdf:type schema:CreativeWork
244 sg:pub.10.1038/srep06697 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012347119
245 https://doi.org/10.1038/srep06697
246 rdf:type schema:CreativeWork
247 sg:pub.10.1038/srep10604 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025197679
248 https://doi.org/10.1038/srep10604
249 rdf:type schema:CreativeWork
250 sg:pub.10.1186/1471-2105-10-275 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024605858
251 https://doi.org/10.1186/1471-2105-10-275
252 rdf:type schema:CreativeWork
253 sg:pub.10.1186/gb-2010-11-3-r25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050509557
254 https://doi.org/10.1186/gb-2010-11-3-r25
255 rdf:type schema:CreativeWork
256 sg:pub.10.1186/gb-2014-15-2-r29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045312009
257 https://doi.org/10.1186/gb-2014-15-2-r29
258 rdf:type schema:CreativeWork
259 https://app.dimensions.ai/details/publication/pub.1078059471 schema:CreativeWork
260 https://app.dimensions.ai/details/publication/pub.1080446225 schema:CreativeWork
261 https://doi.org/10.1002/pmic.201500179 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046487171
262 rdf:type schema:CreativeWork
263 https://doi.org/10.1016/b978-0-12-416555-7.00001-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052423436
264 rdf:type schema:CreativeWork
265 https://doi.org/10.1016/b978-0-12-800101-1.00011-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045436662
266 rdf:type schema:CreativeWork
267 https://doi.org/10.1016/j.biochi.2004.09.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048218799
268 rdf:type schema:CreativeWork
269 https://doi.org/10.1016/j.biochi.2010.02.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034904850
270 rdf:type schema:CreativeWork
271 https://doi.org/10.1016/j.cmet.2012.03.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051276341
272 rdf:type schema:CreativeWork
273 https://doi.org/10.1016/j.jnutbio.2007.09.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034255641
274 rdf:type schema:CreativeWork
275 https://doi.org/10.1016/j.meatsci.2004.11.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022120696
276 rdf:type schema:CreativeWork
277 https://doi.org/10.1016/j.meatsci.2012.09.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003640702
278 rdf:type schema:CreativeWork
279 https://doi.org/10.1016/j.molcel.2013.01.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029235010
280 rdf:type schema:CreativeWork
281 https://doi.org/10.1016/j.nut.2006.06.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029776547
282 rdf:type schema:CreativeWork
283 https://doi.org/10.1016/j.plipres.2010.10.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035064833
284 rdf:type schema:CreativeWork
285 https://doi.org/10.1016/j.tem.2009.05.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050160159
286 rdf:type schema:CreativeWork
287 https://doi.org/10.1016/j.yexcr.2007.07.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011058023
288 rdf:type schema:CreativeWork
289 https://doi.org/10.1017/s0007114512002565 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050308774
290 rdf:type schema:CreativeWork
291 https://doi.org/10.1017/s0954422411000175 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004938160
292 rdf:type schema:CreativeWork
293 https://doi.org/10.1021/jf0009246 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055896283
294 rdf:type schema:CreativeWork
295 https://doi.org/10.1021/jf0481103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055902573
296 rdf:type schema:CreativeWork
297 https://doi.org/10.1021/jf901954r schema:sameAs https://app.dimensions.ai/details/publication/pub.1055926938
298 rdf:type schema:CreativeWork
299 https://doi.org/10.1073/pnas.0506580102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037705714
300 rdf:type schema:CreativeWork
301 https://doi.org/10.1073/pnas.0914005107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011637541
302 rdf:type schema:CreativeWork
303 https://doi.org/10.1074/jbc.m701045200 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040707347
304 rdf:type schema:CreativeWork
305 https://doi.org/10.1079/bjn20061895 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077303393
306 rdf:type schema:CreativeWork
307 https://doi.org/10.1079/pns19720050 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037137050
308 rdf:type schema:CreativeWork
309 https://doi.org/10.1093/bioinformatics/btp616 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023247882
310 rdf:type schema:CreativeWork
311 https://doi.org/10.1093/bioinformatics/btu781 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041244887
312 rdf:type schema:CreativeWork
313 https://doi.org/10.1093/jn/122.3.467 schema:sameAs https://app.dimensions.ai/details/publication/pub.1076919383
314 rdf:type schema:CreativeWork
315 https://doi.org/10.1093/jn/123.11.1939 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082711967
316 rdf:type schema:CreativeWork
317 https://doi.org/10.1093/jn/125.3_suppl.594s schema:sameAs https://app.dimensions.ai/details/publication/pub.1082550318
318 rdf:type schema:CreativeWork
319 https://doi.org/10.1093/jn/125.3_suppl.606s schema:sameAs https://app.dimensions.ai/details/publication/pub.1082550320
320 rdf:type schema:CreativeWork
321 https://doi.org/10.1093/jn/127.5.758 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083095112
322 rdf:type schema:CreativeWork
323 https://doi.org/10.1093/jn/128.7.1084 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083285733
324 rdf:type schema:CreativeWork
325 https://doi.org/10.1093/jn/96.3.303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1081294691
326 rdf:type schema:CreativeWork
327 https://doi.org/10.1093/nar/gkt1168 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023238985
328 rdf:type schema:CreativeWork
329 https://doi.org/10.1093/nar/gkv007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016098431
330 rdf:type schema:CreativeWork
331 https://doi.org/10.1097/mol.0b013e3283613bb7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034869172
332 rdf:type schema:CreativeWork
333 https://doi.org/10.1146/annurev.nutr.27.061406.093726 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004776463
334 rdf:type schema:CreativeWork
335 https://doi.org/10.1152/ajpendo.90207.2008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000726018
336 rdf:type schema:CreativeWork
337 https://doi.org/10.1152/physiolgenomics.00263.2007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002356517
338 rdf:type schema:CreativeWork
339 https://doi.org/10.1177/0884533614550251 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053801329
340 rdf:type schema:CreativeWork
341 https://doi.org/10.1371/journal.pone.0013984 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006850384
342 rdf:type schema:CreativeWork
343 https://doi.org/10.1371/journal.pone.0047303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032907060
344 rdf:type schema:CreativeWork
345 https://doi.org/10.1530/joe-13-0327 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010137250
346 rdf:type schema:CreativeWork
347 https://doi.org/10.2337/db12-1613 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050295819
348 rdf:type schema:CreativeWork
349 https://doi.org/10.2527/jas1962.213558x schema:sameAs https://app.dimensions.ai/details/publication/pub.1070893028
350 rdf:type schema:CreativeWork
351 https://doi.org/10.29074/ascls.23.1.51 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078059471
352 rdf:type schema:CreativeWork
353 https://doi.org/10.5713/ajas.2011.10430 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029355555
354 rdf:type schema:CreativeWork
355 https://www.grid.ac/institutes/grid.27871.3b schema:alternateName Nanjing Agricultural University
356 schema:name Key Laboratory of Meat Processing and Quality Control, MOE; Key Laboratory of Animal Products Processing, MOA; Jiang Synergetic Innovation Center of Meat Processing and Quality Control; Nanjing Agricultural University, Nanjing 210095, P.R. China.
357 rdf:type schema:Organization
358 https://www.grid.ac/institutes/grid.4818.5 schema:alternateName Wageningen University & Research
359 schema:name Nutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen University, Wageningen, the Netherlands.
360 rdf:type schema:Organization
361 https://www.grid.ac/institutes/grid.8273.e schema:alternateName University of East Anglia
362 schema:name Norwich Medical School, University of East Anglia Norwich, Norwich, UK.
363 rdf:type schema:Organization
364 https://www.grid.ac/institutes/grid.89957.3a schema:alternateName Nanjing Medical University
365 schema:name Key Laboratory of Human Function Genomics Jiangsu Province, Nanjing Medical University, Nanjing, 210029, P.R. China.
366 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...